IVGCVSW-6314 Pre-Importing - Create example app

Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
Change-Id: Ibfbc9088aa09d363d67010a695866e68cef823fc

3 files changed, 123 insertions, 1 deletions

diff --git a/include/armnn/IRuntime.hpp b/include/armnn/IRuntime.hpp
index 47bfef588a..014481357d 100644
--- a/include/armnn/IRuntime.hpp
+++ b/include/armnn/IRuntime.hpp
@@ -246,7 +246,7 @@ public:
     /// Allowing for a set of OutputTensors to be imported and mapped once, but used in execution many times.
     /// This function is not thread safe and must not be used while other threads are calling Execute().
     /// Only compatible with AsyncEnabled networks
-    std::vector<ImportedInputId> ImportOutputs(NetworkId networkId, const OutputTensors& outputTensors);
+    std::vector<ImportedOutputId> ImportOutputs(NetworkId networkId, const OutputTensors& outputTensors);
 
     /// Un-import and delete the imported InputTensor/s
     /// This function is not thread safe and must not be used while other threads are calling Execute().
diff --git a/samples/CMakeLists.txt b/samples/CMakeLists.txt
index 7af8b7265a..210dc9c864 100644
--- a/samples/CMakeLists.txt
+++ b/samples/CMakeLists.txt
@@ -16,3 +16,8 @@ if(BUILD_SAMPLE_APP AND ARMCOMPUTECL)
     target_link_libraries(CustomMemoryAllocatorSample armnn ${CMAKE_THREAD_LIBS_INIT})
 endif()
 
+if(BUILD_SAMPLE_APP AND ARMNNREF)
+    add_executable(PreImportMemorySample PreImportMemorySample.cpp)
+    target_link_libraries(PreImportMemorySample armnn ${CMAKE_THREAD_LIBS_INIT})
+endif()
+
diff --git a/samples/PreImportMemorySample.cpp b/samples/PreImportMemorySample.cpp
new file mode 100644
index 0000000000..cf196fd20e
--- /dev/null
+++ b/samples/PreImportMemorySample.cpp
@@ -0,0 +1,117 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <armnn/ArmNN.hpp>
+
+#include <iostream>
+
+// A simple example application to show the usage of Memory Management Pre Importing of Inputs and Outputs. In this
+// sample, the users single input number is added to itself using an add layer and outputted to console as a number
+// that is double the input. The code does not use EnqueueWorkload but instead uses runtime->Execute
+
+int main()
+{
+    using namespace armnn;
+
+    float number;
+    std::cout << "Please enter a number: " << std::endl;
+    std::cin >> number;
+
+    // Turn on logging to standard output
+    // This is useful in this sample so that users can learn more about what is going on
+    armnn::ConfigureLogging(true, false, LogSeverity::Info);
+
+    armnn::IRuntime::CreationOptions options;
+    armnn::IRuntimePtr               runtime(armnn::IRuntime::Create(options));
+
+    armnn::NetworkId   networkIdentifier1 = 0;
+
+    armnn::INetworkPtr testNetwork(armnn::INetwork::Create());
+    auto inputLayer1 = testNetwork->AddInputLayer(0, "input 1 layer");
+    auto inputLayer2 = testNetwork->AddInputLayer(1, "input 2 layer");
+    auto addLayer = testNetwork->AddAdditionLayer("add layer");
+    auto outputLayer = testNetwork->AddOutputLayer(2, "output layer");
+
+    // Set the tensors in the network.
+    TensorInfo tensorInfo{{4}, armnn::DataType::Float32};
+
+    inputLayer1->GetOutputSlot(0).Connect(addLayer->GetInputSlot(0));
+    inputLayer1->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+    inputLayer2->GetOutputSlot(0).Connect(addLayer->GetInputSlot(1));
+    inputLayer2->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+
+    addLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+    addLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+
+    // Set preferred backend to CpuRef
+    std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
+
+    // To hold an eventual error message if loading the network fails
+    std::string er;
+
+    // Initialize network properties with asyncEnabled and MemorySources != MemorySource::Undefined
+    armnn::INetworkProperties networkProperties(true, MemorySource::Malloc, MemorySource::Malloc);
+
+    // Optimize and Load the network into runtime
+    runtime->LoadNetwork(networkIdentifier1,
+                         Optimize(*testNetwork, backends, runtime->GetDeviceSpec()),
+                         er,
+                         networkProperties);
+
+    // Create structures for input & output
+    std::vector<float> inputData1(4, number);
+    std::vector<float> inputData2(4, number);
+    ConstTensor inputTensor1(tensorInfo, inputData1.data());
+    ConstTensor inputTensor2(tensorInfo, inputData2.data());
+
+    std::vector<float> outputData1(4);
+    Tensor outputTensor1{tensorInfo, outputData1.data()};
+
+    // ImportInputs separates the importing and mapping of InputTensors from network execution.
+    // Allowing for a set of InputTensors to be imported and mapped once, but used in execution many times.
+    // ImportInputs is not thread safe and must not be used while other threads are calling Execute().
+    // Only compatible with AsyncEnabled networks
+
+    // PreImport inputTensors giving pre-imported ids of 1 and 2
+    std::vector<ImportedInputId> importedInputVec = runtime->ImportInputs(networkIdentifier1,
+                                                                          {{0, inputTensor1}, {1, inputTensor2}});
+
+    // Create a new unique WorkingMemHandle object. Create multiple handles if you wish to have
+    // overlapped Execution by calling this function from different threads.
+    auto memHandle = runtime->CreateWorkingMemHandle(networkIdentifier1);
+
+    // Execute evaluates a network using input in inputTensors and outputs filled into outputTensors.
+    // This function performs a thread safe execution of the network. Returns once execution is complete.
+    // Will block until this and any other thread using the same workingMem object completes.
+    // Execute with PreImported inputTensor1 as well as Non-PreImported inputTensor2
+    runtime->Execute(*memHandle.get(), {}, {{2, outputTensor1}}, importedInputVec /* pre-imported ids */);
+
+    // ImportOutputs separates the importing and mapping of OutputTensors from network execution.
+    // Allowing for a set of OutputTensors to be imported and mapped once, but used in execution many times.
+    // This function is not thread safe and must not be used while other threads are calling Execute().
+    // Only compatible with AsyncEnabled networks
+    // Provide layerBinding Id to outputTensor1
+    std::pair<LayerBindingId, class Tensor> output1{2, outputTensor1};
+    // PreImport outputTensor1
+    std::vector<ImportedOutputId> importedOutputVec = runtime->ImportOutputs(networkIdentifier1, {output1});
+
+    // Execute with Non-PreImported inputTensor1 as well as PreImported inputTensor2
+    runtime->Execute(*memHandle.get(), {{0, inputTensor1}}, {{2, outputTensor1}}, {1 /* pre-imported id */});
+
+    // Clear the previously PreImportedInput with the network Id and inputIds returned from ImportInputs()
+    // Note: This will happen automatically during destructor of armnn::LoadedNetwork
+    runtime->ClearImportedInputs(networkIdentifier1, importedInputVec);
+
+    // Clear the previously PreImportedOutputs with the network Id and outputIds returned from ImportOutputs()
+    // Note: This will happen automatically during destructor of armnn::LoadedNetwork
+    runtime->ClearImportedOutputs(networkIdentifier1, importedOutputVec);
+
+    // Execute with Non-PreImported inputTensor1, inputTensor2 and the PreImported outputTensor1
+    runtime->Execute(*memHandle.get(), {{0, inputTensor1}, {1, inputTensor2}}, {{2, outputTensor1}});
+
+    std::cout << "Your number was " << outputData1.data()[0] << std::endl;
+
+    return 0;
+}